code: def tokenize_str(texts, tokenizer):
      tokenized_text = []
      for text in texts:
          tok_text = tokenizer.text_to_ids(*text)
          tok_text = [
              chr(token + DEFAULT_TOKEN_OFFSET) for token in tok_text
          ]
          tokenized_text.append(tok_text)
      return tokenized_text
  
file_path: NeMo/scripts/asr_language_modeling/ngram_lm/kenlm_utils.py
imports: import gzip
  import json
  import os
  import numpy
  import torch
  from joblib import Parallel, delayed
  from tqdm.auto import tqdm
  import nemo.collections.asr
  from nemo.collections.asr.parts.submodules.ctc_beam_decoding import DEFAULT_TOKEN_OFFSET
  from nemo.utils import logging
label_desc: Use image node_id 6 for calling a global function with example usage: tokenize_str(texts, tokenizer) and returns: tokenized_text